Frontiers

Computational Frameworks for Decision-Making: From Bayesian Inference to Reinforcement Learning Models

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...
Science Daily

New insight into machine-learning error estimation

Scientists are evaluating machine-learning models using transfer learning principles. Omar Maddouri, a doctoral student in the Department of Electrical and Computer Engineering at Texas A&M University ...
The Mining Journal

The case for Bayesian Learning in mining

Bayesian Learning is becoming more feasible and attracting greater interest in mining. But adopting it also comes with some challenges. For one thing, this is a highly specialised branch of statistics ...
Diginomica

Can Bayesian Networks provide answers when Machine Learning comes up short? It's a question of probabilities

Machine Learning gets all the marketing hype, but are we overlooking Bayesian Networks? Here's a deeper look at why "Bayes Nets" are underrated - especially when it comes to addressing probability and ...
Geeky Gadgets

AI transfer learning from large language models explained

Transfer learning has emerged as a pivotal strategy, particularly in the realm of large language models (LLMs). But what exactly is this concept, and how does it revolutionize the way AI systems learn ...
Android Police

Transfer learning: Everything you need to know about the ML process

I’ve been covering Android since 2022, when I joined Android Police, mostly focusing on AI and everything around Pixel and Galaxy phones. I’ve got a bachelor’s in IT with a major in AI, so I naturally ...
EurekAlert!

Transfer learning offers new insight into machine-learning error estimation

Omar Maddouri, a doctoral student in the Department of Electrical and Computer Engineering at Texas A&M University, is working with Dr. Byung-Jun Yoon, professor, and Dr. Edward Dougherty, Robert M.